58 citations · 198 across the 19 of their papers we have counts for
6 papers · 1 filter
Exact Limits of Inference in Coalescent Models
James E. Johndrow, Julia A. Palacios
Recovery of population size history from molecular sequence data is an important problem in population genetics. Inference commonly relies on a coalescent model linking the populat…
A Decision Theoretic Approach to A/B Testing
David Goldberg, James E. Johndrow
A/B testing is ubiquitous within the machine learning and data science operations of internet companies. Generically, the idea is to perform a statistical test of the hypothesis th…
Theoretical Limits of Record Linkage and Microclustering
James E. Johndrow, Kristian Lum, David B. Dunson
There has been substantial recent interest in record linkage, attempting to group the records pertaining to the same entities from a large database lacking unique identifiers. This…
MCMC for Imbalanced Categorical Data
James E. Johndrow, Aaron Smith, Natesh Pillai +1
Many modern applications collect highly imbalanced categorical data, with some categories relatively rare. Bayesian hierarchical models combat data sparsity by borrowing informatio…
Model-free inference on extreme dependence via waiting times
James E. Johndrow, Robert L. Wolpert
A variety of methods have been proposed for inference about extreme dependence for multivariate or spatially-indexed stochastic processes and time series. Most of these proceed by…
Tensor decompositions and sparse log-linear models
James E. Johndrow, Anirban Battacharya, David B. Dunson
Contingency table analysis routinely relies on log linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a low rank tensor f…